Gomez, Daniel y Montero, Javier (2008) Fuzzy sets in remote sensing classification. Soft Computing, 12 . pp. 243-249. ISSN 1432-7643
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Supervised classification in remote sensing is a very complex problem and involves steps of different nature, including a serious data preprocessing. The final objective can be stated in terms of a classification of isolated pixels between classes, which can be either previously known or not (for example, different land uses), but with no particular shape nither well defined borders. Hence, a fuzzy approach seems natural in order to capture the structure of the image. In this paper we stress that some useful tools for a fuzzy classification can be derived from fuzzy coloring procedures, to be extended in a second stage to the complete non visible spectrum. In fact, the image is considered here as a fuzzy graph defined on the set of pixels, taking advantage of fuzzy numbers in order to summarize information. A fuzzy model is then presented, to be considered as a decision making aid tool. In this way we generalize the classical definition of fuzzy partition due to Ruspini, allowing in addition a first evaluation of the quality of the classification in this way obtained, in terms of three basic indexes (measuring covering, relevance and overlapping of our family of classes).
|Tipo de documento:||Artículo|
|Palabras clave:||Fuzzy classification systems; Remote sensing; Fuzzy graph|
|Materias:||Ciencias > Matemáticas > Estadística matemática|
|Depositado:||10 Sep 2012 09:45|
|Última Modificación:||19 Abr 2016 17:03|
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